23 citations · 54 across the 8 of their papers we have counts for
9 papers
Large-batch Optimization for Dense Visual Predictions
Zeyue Xue, Jianming Liang, Guanglu Song +4
Training a large-scale deep neural network in a large-scale dataset is challenging and time-consuming. The recent breakthrough of large-batch optimization is a promising way to tac…
Unifying Visual Perception by Dispersible Points Learning
Jianming Liang, Guanglu Song, Biao Leng +1
We present a conceptually simple, flexible, and universal visual perception head for variant visual tasks, e.g., classification, object detection, instance segmentation and pose es…
DiRA: Discriminative, Restorative, and Adversarial Learning for Self-supervised Medical Image Analysis
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Michael B. Gotway +1
Discriminative learning, restorative learning, and adversarial learning have proven beneficial for self-supervised learning schemes in computer vision and medical imaging. Existing…
CAiD: Context-Aware Instance Discrimination for Self-supervised Learning in Medical Imaging
Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Michael B. Gotway +1
Recently, self-supervised instance discrimination methods have achieved significant success in learning visual representations from unlabeled photographic images. However, given th…
Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection
Nahid Ul Islam, Shiv Gehlot, Zongwei Zhou +2
Pulmonary embolism (PE) represents a thrombus ("blood clot"), usually originating from a lower extremity vein, that travels to the blood vessels in the lung, causing vascular obstr…
A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis
Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Ruibin Feng +2
Transfer learning from supervised ImageNet models has been frequently used in medical image analysis. Yet, no large-scale evaluation has been conducted to benchmark the efficacy of…